Effective and Economical Content Delivery and Storage Strategies for Cloud Systems

Cloud computing has proved to be an effective infrastructure to host various applications and provide reliable and stable services. Content delivery and storage are two main services provided by the cloud. A high-performance cloud can reduce the cost of both cloud providers and customers, while providing high application performance to cloud clients. Thus, the performance of such cloud-based services is closely related to three issues. First, when delivering contents from the cloud to users or transferring contents between cloud datacenters, it is important to reduce the payment costs and transmission time. Second, when transferring contents between cloud datacenters, it is important to reduce the payment costs to the internet service providers (ISPs). Third, when storing contents in the datacenters, it is crucial to reduce the file read latency and power consumption of the datacenters. In this dissertation, we study how to effectively deliver and store contents on the cloud, with a focus on cloud gaming and video streaming services. In particular, we aim to address three problems. i) Cost-efficient cloud computing system to support thin-client Massively Multiplayer Online Game (MMOG): how to achieve high Quality of Service (QoS) in cloud gaming and reduce the cloud bandwidth consumption; ii) Cost-efficient inter-datacenter video scheduling: how to reduce the bandwidth payment cost by fully utilizing link bandwidth when cloud providers transfer videos between datacenters; iii) Energy-efficient adaptive file replication: how to adapt to time-varying file popularities to achieve a good tradeoff between data availability and efficiency, as well as reduce the power consumption of the datacenters. In this dissertation, we propose methods to solve each of aforementioned challenges on the cloud. As a result, we build a cloud system that has a cost-efficient system to support cloud clients, an inter-datacenter video scheduling algorithm for video transmission on the cloud and an adaptive file replication algorithm for cloud storage system. As a result, the cloud system not only benefits the cloud providers in reducing the cloud cost, but also benefits the cloud customers in reducing their payment cost and improving high cloud application performance (i.e., user experience). Finally, we conducted extensive experiments on many testbeds, including PeerSim, PlanetLab, EC2 and a real-world cluster, which demonstrate the efficiency and effectiveness of our proposed methods. In our future work, we will further study how to further improve user experience in receiving contents and reduce the cost due to content transfer

One-step vapour-phase formation of patternable, electrically conductive, superamphiphobic coatings on fibrous materials

Patternable, electrically conductive coatings having a superhydrophobic and superoleophobic surface have been prepared by one-step vapour-phase polymerisation of polypyrrole in the presence of a fluorinated alkyl silane directly on fibrous substrates. The coated fabrics showed a surface resistance of 0.5-0.8 k&Omega; □-1 with water and hexadecane contact angles of 165&deg; and 154&deg;, respectively.<br /

NMGRS: Neighborhood-based multigranulation rough sets

AbstractRecently, a multigranulation rough set (MGRS) has become a new direction in rough set theory, which is based on multiple binary relations on the universe. However, it is worth noticing that the original MGRS can not be used to discover knowledge from information systems with various domains of attributes. In order to extend the theory of MGRS, the objective of this study is to develop a so-called neighborhood-based multigranulation rough set (NMGRS) in the framework of multigranulation rough sets. Furthermore, by using two different approximating strategies, i.e., seeking common reserving difference and seeking common rejecting difference, we first present optimistic and pessimistic 1-type neighborhood-based multigranulation rough sets and optimistic and pessimistic 2-type neighborhood-based multigranulation rough sets, respectively. Through analyzing several important properties of neighborhood-based multigranulation rough sets, we find that the new rough sets degenerate to the original MGRS when the size of neighborhood equals zero. To obtain covering reducts under neighborhood-based multigranulation rough sets, we then propose a new definition of covering reduct to describe the smallest attribute subset that preserves the consistency of the neighborhood decision system, which can be calculated by Chen’s discernibility matrix approach. These results show that the proposed NMGRS largely extends the theory and application of classical MGRS in the context of multiple granulations

Effect of combination of intravenous general anesthesia with propofol and fentanyl on surgery for aortic dissection repair in patients, and its influence on respiratory and circulatory functions

Purpose: To investigate the effect of application of propofol in combination with fentanyl intravenous anesthesia in interventional surgery for aortic dissection repair, and its influence on respiratory and circulatory functions in patients.Methods: 100 patients undergoing interventional surgery for aortic dissection repair in Xiangyang No. 1 People's Hospital, Hubei University of Medicine, Xiangyang. China from&nbsp; ovember 2018 to May 2020 were assigned equally to control group (CG) and study group (SG). CG received general anesthesia with propofol, while those in SG received combined intravenous general anesthesia with propofol and fentanyl. Time of anesthesia onset, postoperative awakening time, extubation time, respiratory function indicators and circulatory function indicators before operation (T0), and at intraoperative 1 h (T1), intraoperative 2 h (T2) and postoperative 2 h (T3); as well as postoperative VAS pain scores, and Ramsay sedation scores were determined and compared.Results: Compared with CG, SG had shorter anesthesia onset, shorter postoperative awakening and extubation times, and lower postoperative VAS pain and Ramsay sedation scores (p &lt; 0.05). At T1, T2 and T3, indicators of respiratory and circulatory functions were better in SG than in CG (p &gt; 0.05).Conclusion: Combined intravenous general anesthesia using propofol and fentanyl was more effective in interventional surgery for repair of aortic dissection, and it enhanced respiratory and circulatory functions in the patients

Partial exfoliation of layered double hydroxides in DMSO : a route to transparent polymer nanocomposites

Layered double hydroxides (LDHs), either having nitrate counter anions or intercalated with organic molecules, have been for the first time partially exfoliated in dimethyl sulfoxide (DMSO) to form a transparent suspension. Atomic force microscopy (AFM) images showed that both the lateral size and the thickness of the LDH nanoplatelets were decreased after the exfoliation. The organic-LDHs maintained their intercalation characteristics, i.e. the thermal stability improvement of the incorporated organic anions, after the exfoliation in DMSO. Transparent ethylene-vinyl alcohol copolymer (EVOH) nanocomposite films containing partially exfoliated LDHs intercalated with UV absorbers were prepared using DMSO as the processing solvent. As the first reported example of a highly transparent LDH/polymer composite, the obtained composite film had a visible light transmittance of 90% (comparable to that of the pure matrix), was flexible and exhibited an excellent UV-shielding capability and thermal stability. <br /

Lymphoid priming in human bone marrow begins before expression of CD10 with upregulation of L-selectin.

Expression of the cell-surface antigen CD10 has long been used to define the lymphoid commitment of human cells. Here we report a unique lymphoid-primed population in human bone marrow that was generated from hematopoietic stem cells (HSCs) before onset of the expression of CD10 and commitment to the B cell lineage. We identified this subset by high expression of the homing molecule L-selectin (CD62L). CD10(-)CD62L(hi) progenitors had full lymphoid and monocytic potential but lacked erythroid potential. Gene-expression profiling placed the CD10(-)CD62L(hi) population at an intermediate stage of differentiation between HSCs and lineage-negative (Lin(-)) CD34(+)CD10(+) progenitors. CD62L was expressed on immature thymocytes, and its ligands were expressed at the cortico-medullary junction of the thymus, which suggested a possible role for this molecule in homing to the thymus. Our studies identify the earliest stage of lymphoid priming in human bone marrow

Polarization controllable Fresnel lens using dye-doped liquid crystals

A scattering-free, polarization controllable Fresnel zone plate lens is demonstrated using a photo-induced alignment of the dye-doped liquid crystal film. This photo-aligned liquid crystal zone plate provides orthogonal polarization states for odd and even zones. The different focus orders can be separated because of their different polarization states. The fabrication process is relatively simple and the operation voltage is less than 5 V-rms

Azido­(methanol)[N,N′-(o-phenyl­ene)bis­(pyridine-2-carboxamidato)]manganese(III)

In the title complex, [Mn(C18H12N4O2)(N3)(CH4O)], the MnIII ion is in a distorted octa­hedral coordination environment. In the crystal structure, inter­molecular O—H⋯O hydrogen bonds connect mol­ecules into centrosymmetric dimers

Developing an unsupervised real-time anomaly detection scheme for time series with multi-seasonality

On-line detection of anomalies in time series is a key technique used in various event-sensitive scenarios such as robotic system monitoring, smart sensor networks and data center security. However, the increasing diversity of data sources and the variety of demands make this task more challenging than ever. Firstly, the rapid increase in unlabeled data means supervised learning is becoming less suitable in many cases. Secondly, a large portion of time series data have complex seasonality features. Thirdly, on-line anomaly detection needs to be fast and reliable. In light of this, we have developed a prediction-driven, unsupervised anomaly detection scheme, which adopts a backbone model combining the decomposition and the inference of time series data. Further, we propose a novel metric, Local Trend Inconsistency (LTI), and an efficient detection algorithm that computes LTI in a real-time manner and scores each data point robustly in terms of its probability of being anomalous. We have conducted extensive experimentation to evaluate our algorithm with several datasets from both public repositories and production environments. The experimental results show that our scheme outperforms existing representative anomaly detection algorithms in terms of the commonly used metric, Area Under Curve (AUC), while achieving the desired efficiency